Private Peer Feedback as Engagement Driver in Humanitarian Mapping

Prior research suggests that public negative feedback on social knowledge sharing platforms can be powerfully demotivating to newcomers, particularly when it involves peer feedback mechanisms such as ratings and commenting systems. What is the impact on newcomer retention when feedback is private, and from a single peer reviewer? We study these effects using the example of the Humanitarian OpenStreetMap Team, a Wikipedia-style social mapping platform where the review process is closer to a teacher-learner model rather than a public peer review. We observe peer feedback for early contributions by 1,300 newcomers, and assess the impact of different classes of feedback, including performance feedback, corrective feedback, and verbal rewards. We find that verbal rewards and immediate feedback can have a powerful effect on newcomer retention. In order to better support such positive engagement effects, we recommend that system designers conceptually distinguish between mechanisms for quality control and for learner feedback.